The network has 24 recurrent layers, 12 each for the encoder and decoder (fig:network).
Drawing on ideas of deep residual learning from
computer vision [1]}, we make additional connections from the input
to every third hidden layer. To improve learning, the network accesses both the original melody
and the transformed results from previous layers during processing.
The conditional part (chords and mode) is also provided to
the network at every recurrent layer, as extra incoming connections.
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